1. Field of the Invention
The invention relates to machine learning methods for identifying content items that are likely to produce a desired user action when incorporated into a dynamically-generated unit of display, such as a web page.
2. Description of the Related Art
Solutions to the selection of what to display in an electronic medium, such as a web page, has been a problem. For example, an organization that provides news articles may find that the content items to include for display change relatively frequently. In addition, appropriate or desirable content to be displayed for one user may not necessarily be of interest to another user.
In one prior technique, a web page is dynamically generated in response to a page request from a user by associating the user to one of a plurality of contexts and by dynamically generating the web page based on the monitored activity of the users in the associated context. For example, 20 contexts can be used. Each of these contexts vary in selected attributes. The attributes associated with the user are identified and compared to the attributes of the plurality of contexts to find the context to which the user most closely corresponds. The activity of users or a subset of users in a particular context is monitored to determine which content items would likely be of value for presenting to other users of the context.
Disadvantageously, such prior techniques do not provide relatively accurate results in real life because individual users within each context can vary considerably from one another. However, arbitrarily increasing the number of contexts is relatively difficult to implement in practice because the number of users in a context can shrink to a relatively small number with a correspondingly small data population from which to estimate behavior. Such problems have limited the number of contexts for practical use and yet still require relatively large amounts of time-consuming manual intervention to associate the user to the correct context. What is needed is a technique to provide more customizable content without a large amount of human intervention.